Why is “SXSW ” trending ? Exploring Multiple Text Sources for Twitter Topic Summarization

Abstract

User-contributed content is creating a surge on the Internet. A list of “buzzing topics” can effectively monitor the surge and lead people to their topics of interest. Yet a topic phrase alone, such as “SXSW”, can rarely present the information clearly. In this paper, we propose to explore a variety of text sources for summarizing the Twitter topics, includ- ing the tweets, normalized tweets via a ded- icated tweet normalization system, web con- tents linked from the tweets, as well as inte- gration of different text sources. We employ the concept-based optimization framework for topic summarization, and conduct both au- tomatic and human evaluation regarding the summary quality. Performance differences are observed for different input sources and types of topics. We also provide a comprehensive analysis regarding the task challenges